{"id":"W2013160622","doi":"10.1016/j.media.2013.03.009","title":"Tractometer: Towards validation of tractography pipelines","year":2013,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":236,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Artificial intelligence; Seeding; Pattern recognition (psychology); Computer vision; Mathematics; Diffusion MRI; Engineering; Magnetic resonance imaging","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0143582,0.002241593,0.001320651,0.003128567,0.001444544,0.004496794,0.003763148,0.003738218,0.005073681],"category_scores_gemma":[0.07169341,0.00122909,0.001685062,0.001701519,0.001893455,0.003523067,0.00445503,0.003251757,0.003730022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001333272,"about_ca_system_score_gemma":0.004854168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01106513,"about_ca_topic_score_gemma":0.01085913,"domain_scores_codex":[0.9913952,0.003548701,0.0006764515,0.001993141,0.002044751,0.0003418084],"domain_scores_gemma":[0.9692982,0.01451206,0.002134421,0.007130958,0.006202152,0.0007222289],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002087643,0.0006937502,0.02626664,0.001471388,0.001517281,0.0005265205,0.001055608,0.3011978,0.05784342,0.02909708,0.03524721,0.5429957],"study_design_scores_gemma":[0.0001211525,0.0001787546,0.004210405,0.0001193881,0.00008500544,0.0003051778,0.00008978347,0.9475107,0.02847381,0.01111013,0.00771911,0.00007659444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0373368,0.0002745076,0.9271523,0.0003035733,0.0002741557,0.0001916602,0.001661425,0.03178897,0.001016615],"genre_scores_gemma":[0.2503964,0.0002063154,0.7337583,0.0002144917,0.00007126011,0.000387158,0.007134872,0.005650177,0.002180988],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9856418,"threshold_uncertainty_score":0.07593435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04430028071975608,"score_gpt":0.3782283427137563,"score_spread":0.3339280619940003,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}